{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Tutorial 11: time series\n",
    "\n",
    "<img src=\"../../imgs/lightautoml_logo_color.png\" alt=\"LightAutoML logo\" style=\"width:100%;\"/>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "There are some features how LightAutoML makes forecast for time-series tasks:\n",
    "\n",
    "- multi-output strategy for forecasting time series if horizon is more than 1 point (forecast simultaneously over the entire horizon)\n",
    "- global-modelling approach for handling multiple time series (one model for all time series in the dataset)\n",
    "\n",
    "In this tutorial you will learn how to:\n",
    "\n",
    "- run LightAutoML training on data with one or many time series\n",
    "- configure time series features transformers' parameters\n",
    "\n",
    "Official LightAutoML github repository is [here](https://github.com/sb-ai-lab/LightAutoML)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 0. Prerequisites"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 0.0. install LightAutoML"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# !pip install -U lightautoml"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 0.1. Import libraries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Standard python libraries\n",
    "import os\n",
    "import requests\n",
    "\n",
    "# Installed libraries\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from sklearn.metrics import mean_absolute_error\n",
    "\n",
    "# Imports from our package\n",
    "from lightautoml.tasks import Task\n",
    "from lightautoml.addons.autots.base import AutoTS\n",
    "from lightautoml.dataset.roles import DatetimeRole\n",
    "from lightautoml.automl.base import AutoML\n",
    "from lightautoml.ml_algo.boost_cb import BoostCB\n",
    "from lightautoml.ml_algo.linear_sklearn import LinearLBFGS\n",
    "from lightautoml.pipelines.features.lgb_pipeline import LGBSeqSimpleFeatures\n",
    "from lightautoml.pipelines.features.linear_pipeline import LinearTrendFeatures\n",
    "from lightautoml.pipelines.ml.base import MLPipeline\n",
    "from lightautoml.reader.base import DictToPandasSeqReader\n",
    "from lightautoml.automl.blend import WeightedBlender\n",
    "from lightautoml.ml_algo.random_forest import RandomForestSklearn\n",
    "\n",
    "# Disable warnings\n",
    "import warnings\n",
    "warnings.filterwarnings(\"ignore\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 0.2. Constants and functions\n",
    "\n",
    "Here we setup the constants to use in the kernel:\n",
    "- `HORIZON` - number of points to forecast \n",
    "- `TARGET_COLUMN` - target column name in dataset\n",
    "- `DATE_COLUMN` - date column name in dataset\n",
    "- `ID_COLUMN` - id column name in dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "HORIZON = 30\n",
    "TARGET_COLUMN = \"value\"\n",
    "DATE_COLUMN = \"date\"\n",
    "ID_COLUMN = \"ID\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "def draw_raw_ts(\n",
    "    data: pd.DataFrame,\n",
    "    id_column: str,\n",
    "    target_column: str,\n",
    "    date_column: str,\n",
    "    ncols: int = 2,\n",
    "):\n",
    "    \"\"\"Draw graphs of time series with specified parameters.\n",
    "    Args:\n",
    "        - data: pd.DataFrame with time series data\n",
    "        - id_column: id column name in dataset\n",
    "        - target_column: target column name in dataset\n",
    "        - date_column: date column name in dataset\n",
    "        - ncols: number of columns for subplot's grid\n",
    "    \"\"\"\n",
    "    # Initialize grid's shape\n",
    "    num_ts = data[id_column].nunique()\n",
    "    nrows = num_ts // ncols + num_ts % ncols\n",
    "    fig, ax = plt.subplots(\n",
    "        nrows, \n",
    "        ncols, \n",
    "        figsize=(24, 5 * nrows)\n",
    "    )\n",
    "    axes_to_del = nrows * ncols - num_ts\n",
    "    for i in range(axes_to_del):\n",
    "        i_row = (nrows - 1) - i // ncols\n",
    "        i_col = (ncols - 1) - i % ncols\n",
    "        fig.delaxes(ax[i_row][i_col])\n",
    "    \n",
    "    # Draw graphs\n",
    "    for i, ts_id in enumerate(data[id_column].unique()):\n",
    "        i_row = i // ncols\n",
    "        i_col = i % ncols\n",
    "        \n",
    "        ts_df = data[data[id_column] == ts_id]\n",
    "        ax = ax.reshape(nrows, ncols)\n",
    "        ax[i_row, i_col].plot(ts_df[date_column], ts_df[target_column])\n",
    "        ax[i_row, i_col].title.set_text(f\"TS with ID {ts_id}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 0.3. Data loading"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "DATASET_DIR = '../data/'\n",
    "DATASET_NAME = 'ts_data.csv'\n",
    "DATASET_FULLNAME = os.path.join(DATASET_DIR, DATASET_NAME)\n",
    "DATASET_URL = 'https://raw.githubusercontent.com/sb-ai-lab/LightAutoML/master/examples/data/ts_data.csv'\n",
    "if not os.path.exists(DATASET_FULLNAME):\n",
    "    os.makedirs(DATASET_DIR, exist_ok=True)\n",
    "    dataset = requests.get(DATASET_URL).text\n",
    "    with open(DATASET_FULLNAME, 'w') as output:\n",
    "        output.write(dataset)\n",
    "\n",
    "df = pd.read_csv(DATASET_FULLNAME)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>date</th>\n",
       "      <th>value</th>\n",
       "      <th>ID</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2020-01-01</td>\n",
       "      <td>2.100760</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2020-01-02</td>\n",
       "      <td>2.106072</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2020-01-03</td>\n",
       "      <td>2.291461</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2020-01-04</td>\n",
       "      <td>2.322224</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2020-01-05</td>\n",
       "      <td>2.140932</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        date     value  ID\n",
       "0 2020-01-01  2.100760   0\n",
       "1 2020-01-02  2.106072   0\n",
       "2 2020-01-03  2.291461   0\n",
       "3 2020-01-04  2.322224   0\n",
       "4 2020-01-05  2.140932   0"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "data shape: (10000, 3)\n",
      "number of time series in data: 5\n"
     ]
    }
   ],
   "source": [
    "df[DATE_COLUMN] = pd.to_datetime(df[DATE_COLUMN])\n",
    "display(df.head())\n",
    "print(f\"data shape: {df.shape}\")\n",
    "print(f\"number of time series in data: {df[ID_COLUMN].nunique()}\")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This data is simulated and presented time series, contained such components as trend, seasonality, events and future reg.\n",
    "\n",
    "On the cell below we draw our time series:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1728x1080 with 5 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "draw_raw_ts(df, ID_COLUMN, TARGET_COLUMN, DATE_COLUMN)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 0.4. Data splitting for train-holdout"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's make forecast of 30 next points. So, we should make train-test-split for each times series in our data. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Assume, that our time series are aligned and have identical timestamps.\n",
    "test_start = df[df[ID_COLUMN] == 0][DATE_COLUMN].values[-HORIZON]  \n",
    "\n",
    "train = df[df[DATE_COLUMN] < test_start].copy()\n",
    "test = df[df[DATE_COLUMN] >= test_start].copy()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1. Task definition"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 1.1. Task type"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "On the cell below we create ```Task``` object - the class to setup what task LightAutoML model should solve with specific loss and metric if necessary (more info can be found [here](https://lightautoml.readthedocs.io/en/latest/pages/modules/generated/lightautoml.tasks.base.Task.html#lightautoml.tasks.base.Task) in our documentation). For time series forecasting it should set as \"multi:reg\":"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "multi:reg isn`t supported in lgb\n"
     ]
    }
   ],
   "source": [
    "task = Task(\"multi:reg\", greater_is_better=False, metric=\"mae\", loss=\"mae\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 1.2. Feature roles setup"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The only role you must setup is ```\"target\"``` role, everything else (date, categorical, etc.) is up to user. \n",
    "\n",
    "But if we have several time series in data, it is recommended to setup ```\"id\"``` role to group our observations. Also we can define seasonal features through `DatetimeRole`. Valid are: `y`, `m`, `d`, `wd`, `hour`, `min`, `sec`, `ms`, `ns`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "univariate_roles = {\n",
    "    \"target\": TARGET_COLUMN,\n",
    "    DatetimeRole(seasonality=('d', 'm', 'wd'), base_date=True): DATE_COLUMN,\n",
    "}\n",
    "\n",
    "global_modelling_roles = {\n",
    "    \"target\": TARGET_COLUMN,\n",
    "    DatetimeRole(seasonality=('d', 'm', 'wd'), base_date=True): DATE_COLUMN,\n",
    "    \"id\": ID_COLUMN\n",
    "}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 1.3. LightAutoML (AutoTS) model creation"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In this part we are going to create LightAutoML model with ```AutoTS``` class."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The params we can setup:\n",
    "- ```task``` - the type of the ML task (we defined it earlier)\n",
    "- ```seq_params``` - parameter for Reader object, which works on the first step of data preparation:\n",
    "  - ```case``` - the type of problem we are solving (```next_values```: prediction of next values)\n",
    "  - ```n_target``` - forecasting horizon\n",
    "  - ```history``` - history size for feature generating (i.e., features for observation $y_t$ are counted from observations ($y_{t-history}$, ..., $y_{t-1}$))\n",
    "  - ```step``` - in how many points to take the next observation in the training sample (the higher the step value --> the fewer observations fall into the training sample)\n",
    "  - ```test_last``` - technical parameter: test data are built by the last observation from the training sample\n",
    "  - ```from_last``` - technical parameter: build train features from last possible observation.\n",
    "- ```transformers_params``` - parameter for Transformer objects, which are needed to make features from raw time series\n",
    "  - ```lag_features``` - *bool/int/list/array*: lags to make lag features for features other than date\n",
    "  - ```lag_time_features``` - *bool/int/list/array*: lags to make lag features for date features\n",
    "  - ```diff_features``` - *bool/int/list/array*: lags to make difference features for features other than date\n",
    "- ```trend_params``` - parameter for TrendModel object, which is needed to detrend the time series before using the main AutoML class "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "__Note:__ Parameters within the transformers_params may be configured as True/False, or integer, list, numpy-array:\n",
    "- __True__: use default values (lag_other_features=30, lag_time_features=30, diff_features=7)\n",
    "- __int__: use all lags and diffs up to the input number (range)\n",
    "- __list__: use certain lags and diffs specified in the list"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "There are some figures which can be helpful for better understanding these params:"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Firstly, let's generalise regression task of time series forecasting: \n",
    "- with known values for timestamps from $T_{N+1}$ to $T_0$ we should predict ones for timestamps $T_{1}, ..., T_{F}$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<img src=\"../../imgs/tutorial_11_general_problem_statement.png\" alt=\"Time series general problem statement\"/>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- assume that $N=10$ and $F = 3$ and get train and test index arrays for values in time series:"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<img src=\"../../imgs/tutorial_11_case_problem_statement.png\" alt=\"Time series case problem statement\"/>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Firstly, the graph below is about ```history``` and ```step``` parameters:"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<img src=\"../../imgs/tutorial_11_history_step_params.png\" alt=\"History and step params description\"/>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now let's take the first case and understand how ```transformers_params``` work and how train and test samples look like after transformations:"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<img src=\"../../imgs/tutorial_11_transformers_params.png\" alt=\"Transformers params description\"/>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "seq_params = {\n",
    "    \"seq0\": {\n",
    "        \"case\": \"next_values\",                  \n",
    "        \"params\": {\n",
    "            \"n_target\": HORIZON,                \n",
    "            \"history\": HORIZON,                              \n",
    "            \"step\": 1, \n",
    "            \"from_last\": True,\n",
    "            \"test_last\": True\n",
    "        }\n",
    "    }\n",
    "}\n",
    "\n",
    "transformers_params = {\n",
    "    \"lag_features\": 30,\n",
    "    \"lag_time_features\": 30,\n",
    "    \"diff_features\": [1, 2, 3, 4, 5, 6, 7, 14],\n",
    "}\n",
    "\n",
    "# You can try specify parameters for trend model too\n",
    "# trend_params = {\n",
    "#     'trend': False,\n",
    "#     'train_on_trend': False,\n",
    "#     'trend_type': 'decompose',  # one of 'decompose', 'decompose_STL', 'linear' or 'rolling'\n",
    "#     'trend_size': 1, \n",
    "#     'decompose_period': 30, \n",
    "#     'detect_step_quantile': 0.01, \n",
    "#     'detect_step_window': 1, \n",
    "#     'detect_step_threshold': 0.7,\n",
    "#     'rolling_size': 1, \n",
    "#     'verbose': 0\n",
    "# }\n",
    "\n",
    "automl = AutoTS(\n",
    "    task,\n",
    "    reader_params = {\n",
    "        \"seq_params\": seq_params\n",
    "    },\n",
    "    time_series_trend_params={\n",
    "        \"trend\": False,\n",
    "    },\n",
    "    time_series_pipeline_params=transformers_params\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Important note**: `reader_params`, `time_series_trend_params`, `time_series_pipeline_params`, `general_params` keys are the YAML config keys, which is used inside `TabularAutoML` preset. More details on its structure with explanation comments can be found inside the `lightautoml/automl/presets/time_series_config.yaml` file. Each key from this config can be modified with user settings during both to providing .yml file and modifying while AutoTS class initialization like in the cell above. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2. AutoML training"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2.1. Univariate LightAutoML"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "# leave only ts with ID = 4\n",
    "ID = 4\n",
    "\n",
    "univariate_train = train[train[ID_COLUMN] == ID].drop(\"ID\", axis=1)\n",
    "univariate_test = test[test[ID_COLUMN] == ID].drop(\"ID\", axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "os.environ[\"CUDA_DEVICE_ORDER\"] = \"PCI_BUS_ID\"\n",
    "os.environ[\"CUDA_VISIBLE_DEVICES\"] = \"1\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[10:24:17] Stdout logging level is DEBUG.\n",
      "[10:24:17] Task: multi:reg\n",
      "\n",
      "[10:24:17] Start automl preset with listed constraints:\n",
      "[10:24:17] - time: 3600.00 seconds\n",
      "[10:24:17] - CPU: 4 cores\n",
      "[10:24:17] - memory: 16 GB\n",
      "\n",
      "[17:58:26] Layer \u001b[1m1\u001b[0m train process start. Time left 3599.96 secs\n",
      "[17:58:26] Start fitting \u001b[1mLvl_0_Pipe_0_Mod_0_RFSklearn\u001b[0m ...\n",
      "[17:58:26] Training params: {'bootstrap': True, 'ccp_alpha': 0.0, 'max_depth': None, 'max_features': 'sqrt', 'max_leaf_nodes': None, 'max_samples': None, 'min_samples_leaf': 32, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 500, 'n_jobs': 4, 'oob_score': False, 'random_state': 42, 'warm_start': False, 'verbose': 0, 'criterion': 'mse'}\n",
      "[17:58:26] ===== Start working with \u001b[1mfold 0\u001b[0m for \u001b[1mLvl_0_Pipe_0_Mod_0_RFSklearn\u001b[0m =====\n",
      "[17:58:27] Score for RF model: -0.474507\n",
      "[17:58:27] ===== Start working with \u001b[1mfold 1\u001b[0m for \u001b[1mLvl_0_Pipe_0_Mod_0_RFSklearn\u001b[0m =====\n",
      "[17:58:28] Score for RF model: -0.468268\n",
      "[17:58:28] Fitting \u001b[1mLvl_0_Pipe_0_Mod_0_RFSklearn\u001b[0m finished. score = \u001b[1m-0.4713888963184421\u001b[0m\n",
      "[17:58:28] \u001b[1mLvl_0_Pipe_0_Mod_0_RFSklearn\u001b[0m fitting and predicting completed\n",
      "[17:58:28] Time left 3598.34 secs\n",
      "\n",
      "[17:58:28] Start fitting \u001b[1mLvl_0_Pipe_1_Mod_0_LinearL2\u001b[0m ...\n",
      "[17:58:28] Training params: {'tol': 1e-06, 'max_iter': 100, 'cs': [1e-05, 5e-05, 0.0001, 0.0005, 0.001, 0.005, 0.01, 0.05, 0.1, 0.5, 1, 5, 10, 50, 100, 500, 1000, 5000, 10000, 50000, 100000], 'early_stopping': 2, 'categorical_idx': [], 'embed_sizes': (), 'data_size': 188}\n",
      "[17:58:28] ===== Start working with \u001b[1mfold 0\u001b[0m for \u001b[1mLvl_0_Pipe_1_Mod_0_LinearL2\u001b[0m =====\n",
      "[17:58:28] Linear model: C = 1e-05 score = -0.6003076791232048\n",
      "[17:58:28] Linear model: C = 5e-05 score = -0.5183533156110102\n",
      "[17:58:29] Linear model: C = 0.0001 score = -0.46330821971023245\n",
      "[17:58:29] Linear model: C = 0.0005 score = -0.36810350419844357\n",
      "[17:58:29] Linear model: C = 0.001 score = -0.35480725252195533\n",
      "[17:58:29] Linear model: C = 0.005 score = -0.3475977814992737\n",
      "[17:58:29] Linear model: C = 0.01 score = -0.3480328256824163\n",
      "[17:58:30] Linear model: C = 0.05 score = -0.3484652342803444\n",
      "[17:58:30] ===== Start working with \u001b[1mfold 1\u001b[0m for \u001b[1mLvl_0_Pipe_1_Mod_0_LinearL2\u001b[0m =====\n",
      "[17:58:30] Linear model: C = 1e-05 score = -0.6028475283394467\n",
      "[17:58:30] Linear model: C = 5e-05 score = -0.5207041477349572\n",
      "[17:58:30] Linear model: C = 0.0001 score = -0.4659881593860412\n",
      "[17:58:30] Linear model: C = 0.0005 score = -0.3684143016750015\n",
      "[17:58:31] Linear model: C = 0.001 score = -0.3556188196228592\n",
      "[17:58:31] Linear model: C = 0.005 score = -0.34978738837360196\n",
      "[17:58:31] Linear model: C = 0.01 score = -0.3501108550228322\n",
      "[17:58:31] Linear model: C = 0.05 score = -0.35125563103009994\n",
      "[17:58:31] Fitting \u001b[1mLvl_0_Pipe_1_Mod_0_LinearL2\u001b[0m finished. score = \u001b[1m-0.34869201204086625\u001b[0m\n",
      "[17:58:31] \u001b[1mLvl_0_Pipe_1_Mod_0_LinearL2\u001b[0m fitting and predicting completed\n",
      "[17:58:31] Time left 3594.93 secs\n",
      "\n",
      "[17:58:31] Start fitting \u001b[1mLvl_0_Pipe_2_Mod_0_CatBoost\u001b[0m ...\n",
      "[17:58:31] Training params: {'task_type': 'GPU', 'thread_count': 4, 'random_seed': 42, 'num_trees': 3000, 'learning_rate': 0.03, 'l2_leaf_reg': 0.01, 'bootstrap_type': 'Bernoulli', 'grow_policy': 'SymmetricTree', 'max_depth': 5, 'min_data_in_leaf': 1, 'one_hot_max_size': 10, 'fold_permutation_block': 1, 'boosting_type': 'Plain', 'boost_from_average': True, 'od_type': 'Iter', 'od_wait': 100, 'max_bin': 32, 'feature_border_type': 'GreedyLogSum', 'nan_mode': 'Min', 'verbose': 100, 'allow_writing_files': False, 'devices': '0'}\n",
      "[17:58:31] ===== Start working with \u001b[1mfold 0\u001b[0m for \u001b[1mLvl_0_Pipe_2_Mod_0_CatBoost\u001b[0m =====\n",
      "[17:58:32] 0:\tlearn: 4.4726230\ttest: 4.4551552\tbest: 4.4551552 (0)\ttotal: 59.3ms\tremaining: 2m 57s\n",
      "[17:58:33] 100:\tlearn: 2.5849946\ttest: 2.8315490\tbest: 2.8315490 (100)\ttotal: 1.29s\tremaining: 36.9s\n",
      "[17:58:34] 200:\tlearn: 1.8855638\ttest: 2.2618428\tbest: 2.2618428 (200)\ttotal: 2.5s\tremaining: 34.7s\n",
      "[17:58:35] 300:\tlearn: 1.5189472\ttest: 1.9874703\tbest: 1.9874703 (300)\ttotal: 3.72s\tremaining: 33.3s\n",
      "[17:58:36] 400:\tlearn: 1.2936364\ttest: 1.8444599\tbest: 1.8444599 (400)\ttotal: 4.9s\tremaining: 31.8s\n",
      "[17:58:38] 500:\tlearn: 1.1450053\ttest: 1.7661319\tbest: 1.7661319 (500)\ttotal: 6.12s\tremaining: 30.5s\n",
      "[17:58:39] 600:\tlearn: 1.0355444\ttest: 1.7198144\tbest: 1.7198144 (600)\ttotal: 7.27s\tremaining: 29s\n",
      "[17:58:40] 700:\tlearn: 0.9461529\ttest: 1.6905038\tbest: 1.6905038 (700)\ttotal: 8.49s\tremaining: 27.8s\n",
      "[17:58:41] 800:\tlearn: 0.8698428\ttest: 1.6713547\tbest: 1.6713547 (800)\ttotal: 9.64s\tremaining: 26.5s\n",
      "[17:58:42] 900:\tlearn: 0.8034182\ttest: 1.6592994\tbest: 1.6592994 (900)\ttotal: 10.8s\tremaining: 25.2s\n",
      "[17:58:44] 1000:\tlearn: 0.7435150\ttest: 1.6494466\tbest: 1.6493530 (997)\ttotal: 12s\tremaining: 23.9s\n",
      "[17:58:45] 1100:\tlearn: 0.6882164\ttest: 1.6402117\tbest: 1.6402017 (1099)\ttotal: 13.2s\tremaining: 22.7s\n",
      "[17:58:46] 1200:\tlearn: 0.6392184\ttest: 1.6336748\tbest: 1.6336748 (1200)\ttotal: 14.4s\tremaining: 21.6s\n",
      "[17:58:47] 1300:\tlearn: 0.5943148\ttest: 1.6284005\tbest: 1.6283444 (1299)\ttotal: 15.7s\tremaining: 20.5s\n",
      "[17:58:48] 1400:\tlearn: 0.5537223\ttest: 1.6237273\tbest: 1.6237273 (1400)\ttotal: 16.9s\tremaining: 19.3s\n",
      "[17:58:50] 1500:\tlearn: 0.5174100\ttest: 1.6217630\tbest: 1.6217572 (1499)\ttotal: 18.1s\tremaining: 18s\n",
      "[17:58:51] 1600:\tlearn: 0.4829392\ttest: 1.6189425\tbest: 1.6189425 (1600)\ttotal: 19.3s\tremaining: 16.8s\n",
      "[17:58:52] 1700:\tlearn: 0.4513613\ttest: 1.6168994\tbest: 1.6168994 (1700)\ttotal: 20.4s\tremaining: 15.6s\n",
      "[17:58:53] 1800:\tlearn: 0.4221131\ttest: 1.6147198\tbest: 1.6147198 (1800)\ttotal: 21.6s\tremaining: 14.4s\n",
      "[17:58:55] 1900:\tlearn: 0.3947037\ttest: 1.6129983\tbest: 1.6129983 (1900)\ttotal: 22.9s\tremaining: 13.2s\n",
      "[17:58:56] 2000:\tlearn: 0.3704698\ttest: 1.6118408\tbest: 1.6118361 (1999)\ttotal: 24.1s\tremaining: 12s\n",
      "[17:58:57] 2100:\tlearn: 0.3473040\ttest: 1.6108620\tbest: 1.6108613 (2099)\ttotal: 25.2s\tremaining: 10.8s\n",
      "[17:58:58] 2200:\tlearn: 0.3258960\ttest: 1.6102695\tbest: 1.6102651 (2188)\ttotal: 26.4s\tremaining: 9.59s\n",
      "[17:58:59] 2300:\tlearn: 0.3054025\ttest: 1.6097875\tbest: 1.6097492 (2296)\ttotal: 27.6s\tremaining: 8.38s\n",
      "[17:59:00] 2400:\tlearn: 0.2867054\ttest: 1.6090802\tbest: 1.6090795 (2398)\ttotal: 28.8s\tremaining: 7.17s\n",
      "[17:59:02] 2500:\tlearn: 0.2689507\ttest: 1.6081654\tbest: 1.6081654 (2500)\ttotal: 29.9s\tremaining: 5.97s\n",
      "[17:59:03] 2600:\tlearn: 0.2525349\ttest: 1.6076868\tbest: 1.6076019 (2590)\ttotal: 31.1s\tremaining: 4.77s\n",
      "[17:59:04] 2700:\tlearn: 0.2377121\ttest: 1.6073861\tbest: 1.6073861 (2700)\ttotal: 32.3s\tremaining: 3.57s\n",
      "[17:59:05] 2800:\tlearn: 0.2229549\ttest: 1.6071654\tbest: 1.6071654 (2800)\ttotal: 33.4s\tremaining: 2.38s\n",
      "[17:59:06] 2900:\tlearn: 0.2094542\ttest: 1.6066872\tbest: 1.6066869 (2899)\ttotal: 34.6s\tremaining: 1.18s\n",
      "[17:59:07] 2999:\tlearn: 0.1970519\ttest: 1.6066699\tbest: 1.6066511 (2993)\ttotal: 35.8s\tremaining: 0us\n",
      "[17:59:07] bestTest = 1.606651141\n",
      "[17:59:07] bestIteration = 2993\n",
      "[17:59:07] Shrink model to first 2994 iterations.\n",
      "[17:59:08] ===== Start working with \u001b[1mfold 1\u001b[0m for \u001b[1mLvl_0_Pipe_2_Mod_0_CatBoost\u001b[0m =====\n",
      "[17:59:08] 0:\tlearn: 4.4577437\ttest: 4.4867925\tbest: 4.4867925 (0)\ttotal: 15.6ms\tremaining: 46.8s\n",
      "[17:59:09] 100:\tlearn: 2.6137326\ttest: 2.8394343\tbest: 2.8394343 (100)\ttotal: 1.19s\tremaining: 34.2s\n",
      "[17:59:10] 200:\tlearn: 1.8909167\ttest: 2.2558778\tbest: 2.2558778 (200)\ttotal: 2.38s\tremaining: 33.2s\n",
      "[17:59:11] 300:\tlearn: 1.4986037\ttest: 1.9673679\tbest: 1.9673679 (300)\ttotal: 3.58s\tremaining: 32.1s\n",
      "[17:59:12] 400:\tlearn: 1.2687985\ttest: 1.8194061\tbest: 1.8194061 (400)\ttotal: 4.75s\tremaining: 30.8s\n",
      "[17:59:14] 500:\tlearn: 1.1222801\ttest: 1.7438983\tbest: 1.7438983 (500)\ttotal: 6.06s\tremaining: 30.2s\n",
      "[17:59:15] 600:\tlearn: 1.0116269\ttest: 1.6987285\tbest: 1.6987285 (600)\ttotal: 7.25s\tremaining: 29s\n",
      "[17:59:16] 700:\tlearn: 0.9254741\ttest: 1.6695112\tbest: 1.6695112 (700)\ttotal: 8.44s\tremaining: 27.7s\n",
      "[17:59:17] 800:\tlearn: 0.8495263\ttest: 1.6502003\tbest: 1.6501991 (799)\ttotal: 9.64s\tremaining: 26.5s\n",
      "[17:59:18] 900:\tlearn: 0.7812408\ttest: 1.6338258\tbest: 1.6337881 (899)\ttotal: 10.8s\tremaining: 25.2s\n",
      "[17:59:20] 1000:\tlearn: 0.7249770\ttest: 1.6227465\tbest: 1.6227465 (1000)\ttotal: 12s\tremaining: 24s\n",
      "[17:59:21] 1100:\tlearn: 0.6742388\ttest: 1.6164241\tbest: 1.6164241 (1100)\ttotal: 13.2s\tremaining: 22.8s\n",
      "[17:59:22] 1200:\tlearn: 0.6261038\ttest: 1.6104160\tbest: 1.6103175 (1199)\ttotal: 14.4s\tremaining: 21.6s\n",
      "[17:59:23] 1300:\tlearn: 0.5812009\ttest: 1.6058196\tbest: 1.6058196 (1300)\ttotal: 15.6s\tremaining: 20.3s\n",
      "[17:59:24] 1400:\tlearn: 0.5414582\ttest: 1.6023364\tbest: 1.6023274 (1396)\ttotal: 16.8s\tremaining: 19.1s\n",
      "[17:59:26] 1500:\tlearn: 0.5047374\ttest: 1.5997954\tbest: 1.5997954 (1500)\ttotal: 17.9s\tremaining: 17.9s\n",
      "[17:59:27] 1600:\tlearn: 0.4710768\ttest: 1.5971879\tbest: 1.5971516 (1599)\ttotal: 19.1s\tremaining: 16.7s\n",
      "[17:59:28] 1700:\tlearn: 0.4406853\ttest: 1.5948181\tbest: 1.5948181 (1700)\ttotal: 20.3s\tremaining: 15.5s\n",
      "[17:59:29] 1800:\tlearn: 0.4122589\ttest: 1.5932432\tbest: 1.5932432 (1800)\ttotal: 21.5s\tremaining: 14.3s\n",
      "[17:59:30] 1900:\tlearn: 0.3856189\ttest: 1.5923377\tbest: 1.5922775 (1884)\ttotal: 22.7s\tremaining: 13.1s\n",
      "[17:59:31] 2000:\tlearn: 0.3613043\ttest: 1.5910058\tbest: 1.5910058 (2000)\ttotal: 23.8s\tremaining: 11.9s\n",
      "[17:59:33] 2100:\tlearn: 0.3383675\ttest: 1.5898274\tbest: 1.5898274 (2100)\ttotal: 25s\tremaining: 10.7s\n",
      "[17:59:34] 2200:\tlearn: 0.3172203\ttest: 1.5889919\tbest: 1.5889524 (2197)\ttotal: 26.2s\tremaining: 9.51s\n",
      "[17:59:35] 2300:\tlearn: 0.2974622\ttest: 1.5885660\tbest: 1.5885542 (2299)\ttotal: 27.4s\tremaining: 8.32s\n",
      "[17:59:36] 2400:\tlearn: 0.2794474\ttest: 1.5876316\tbest: 1.5876312 (2399)\ttotal: 28.6s\tremaining: 7.13s\n",
      "[17:59:37] 2500:\tlearn: 0.2620195\ttest: 1.5870893\tbest: 1.5870893 (2500)\ttotal: 29.8s\tremaining: 5.94s\n",
      "[17:59:39] 2600:\tlearn: 0.2461638\ttest: 1.5866054\tbest: 1.5865939 (2598)\ttotal: 30.9s\tremaining: 4.75s\n",
      "[17:59:40] 2700:\tlearn: 0.2310694\ttest: 1.5863323\tbest: 1.5863064 (2696)\ttotal: 32.1s\tremaining: 3.55s\n",
      "[17:59:41] 2800:\tlearn: 0.2173924\ttest: 1.5859899\tbest: 1.5859823 (2799)\ttotal: 33.3s\tremaining: 2.37s\n",
      "[17:59:42] 2900:\tlearn: 0.2046222\ttest: 1.5855330\tbest: 1.5855330 (2900)\ttotal: 34.5s\tremaining: 1.18s\n",
      "[17:59:43] 2999:\tlearn: 0.1924596\ttest: 1.5853173\tbest: 1.5852992 (2953)\ttotal: 35.6s\tremaining: 0us\n",
      "[17:59:43] bestTest = 1.585299221\n",
      "[17:59:43] bestIteration = 2953\n",
      "[17:59:43] Shrink model to first 2954 iterations.\n",
      "[17:59:43] Fitting \u001b[1mLvl_0_Pipe_2_Mod_0_CatBoost\u001b[0m finished. score = \u001b[1m-0.22094300934924996\u001b[0m\n",
      "[17:59:43] \u001b[1mLvl_0_Pipe_2_Mod_0_CatBoost\u001b[0m fitting and predicting completed\n",
      "[17:59:43] Time left 3522.77 secs\n",
      "\n",
      "[17:59:43] \u001b[1mLayer 1 training completed.\u001b[0m\n",
      "\n",
      "[17:59:43] Blending: optimization starts with equal weights and score \u001b[1m-0.3009012970426841\u001b[0m\n",
      "[17:59:43] Blending: iteration \u001b[1m0\u001b[0m: score = \u001b[1m-0.22094300934924996\u001b[0m, weights = \u001b[1m[0. 0. 1.]\u001b[0m\n",
      "[17:59:43] Blending: iteration \u001b[1m1\u001b[0m: score = \u001b[1m-0.22094300934924996\u001b[0m, weights = \u001b[1m[0. 0. 1.]\u001b[0m\n",
      "[17:59:43] Blending: no score update. Terminated\n",
      "\n",
      "[17:59:43] \u001b[1mAutoml preset training completed in 77.27 seconds\u001b[0m\n",
      "\n",
      "[10:25:54] Model description:\n",
      "Final prediction for new objects (level 0) = \n",
      "\t 1.00000 * (2 averaged models Lvl_0_Pipe_2_Mod_0_CatBoost) \n",
      "\n"
     ]
    }
   ],
   "source": [
    "univariate_train_pred, _ = automl.fit_predict(univariate_train, univariate_roles, verbose=4)\n",
    "univariate_forecast, _ = automl.predict(univariate_train)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's take a look on forecasts of univariate time series and check MAE"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[3.44697142 3.073035   2.49203897 2.1270709  2.29297566 2.70116901\n",
      " 2.83488226 2.49551201 2.16700649 1.99528813 2.31517577 2.87421489\n",
      " 3.00472379 2.59042096 1.8664093  1.47073889 1.81992817 2.58693051\n",
      " 3.36398268 3.59384632 3.24508047 2.63568759 2.20735097 1.9374007\n",
      " 1.74858916 1.72028816 1.79335809 2.08676887 2.57858872 3.18161464] \n",
      "\n",
      "MAE: 0.22544950642226508\n"
     ]
    }
   ],
   "source": [
    "print(univariate_forecast, \"\\n\")\n",
    "print(f\"MAE: {mean_absolute_error(univariate_test.value, univariate_forecast)}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Get a graph of model's predictions in comparison with true values "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 936x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "last_N = min(len(train), 100)\n",
    "\n",
    "fig = plt.figure(figsize=(13, 5))\n",
    "plt.plot(\n",
    "    univariate_train[DATE_COLUMN][-last_N:], \n",
    "    univariate_train[TARGET_COLUMN][-last_N:], \n",
    "    c=\"#003865\", \n",
    "    label=\"train\"\n",
    ")\n",
    "plt.plot(\n",
    "    univariate_test[DATE_COLUMN], \n",
    "    univariate_test[TARGET_COLUMN], \n",
    "    c=\"#EF5B0C\", \n",
    "    label=\"test\", \n",
    "    marker=\"o\", \n",
    "    markersize=4\n",
    ")\n",
    "plt.plot(\n",
    "    univariate_test[DATE_COLUMN], \n",
    "    univariate_forecast, \n",
    "    c=\"#3CCF4E\", \n",
    "    label=\"forecast\", \n",
    "    marker=\"o\", \n",
    "    markersize=4\n",
    ")\n",
    "\n",
    "plt.xlabel(\"Date\")\n",
    "plt.ylabel(\"Value\")\n",
    "plt.title(f\"Train, test and forecasts of LightAutoML (univariate) for TS with ID {ID}\")\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "One by one make forecasts for all time series in dataset and collect them to a new pd.DataFrame:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "ID_array = np.repeat(df[ID_COLUMN].unique(), HORIZON)\n",
    "test_array = np.array([])\n",
    "pred_array = np.array([])\n",
    "date_array = np.array([]).astype(\"datetime64\")\n",
    "\n",
    "for ts_id in df[ID_COLUMN].unique():\n",
    "    univariate_train = train[train[ID_COLUMN] == ts_id]\n",
    "    univariate_test = test[test[ID_COLUMN] == ts_id]\n",
    "    \n",
    "    # Model fit_predict\n",
    "    _, _ = automl.fit_predict(univariate_train, univariate_roles)\n",
    "    univariate_forecast, _ = automl.predict(univariate_train)\n",
    "    pred_array = np.append(pred_array, univariate_forecast)\n",
    "    test_array = np.append(test_array, univariate_test[TARGET_COLUMN].values)\n",
    "    date_array = np.append(date_array, univariate_test[DATE_COLUMN].values)\n",
    "    \n",
    "# Collect results\n",
    "res_df_dict = {\n",
    "    \"ID\": ID_array,\n",
    "    \"pred\": pred_array,\n",
    "    \"date\": date_array,\n",
    "    \"test\": test_array\n",
    "}\n",
    "\n",
    "res_df_univariate = pd.DataFrame(res_df_dict)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ID</th>\n",
       "      <th>pred</th>\n",
       "      <th>date</th>\n",
       "      <th>test</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>2.427282</td>\n",
       "      <td>2025-05-24</td>\n",
       "      <td>1.581092</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0</td>\n",
       "      <td>3.297728</td>\n",
       "      <td>2025-05-25</td>\n",
       "      <td>2.376163</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0</td>\n",
       "      <td>3.508930</td>\n",
       "      <td>2025-05-26</td>\n",
       "      <td>2.627754</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0</td>\n",
       "      <td>3.071776</td>\n",
       "      <td>2025-05-27</td>\n",
       "      <td>2.105468</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0</td>\n",
       "      <td>2.333910</td>\n",
       "      <td>2025-05-28</td>\n",
       "      <td>1.969833</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   ID      pred       date      test\n",
       "0   0  2.427282 2025-05-24  1.581092\n",
       "1   0  3.297728 2025-05-25  2.376163\n",
       "2   0  3.508930 2025-05-26  2.627754\n",
       "3   0  3.071776 2025-05-27  2.105468\n",
       "4   0  2.333910 2025-05-28  1.969833"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "res_df_univariate.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Check MAE for all time series:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ID</th>\n",
       "      <th>MAE_univariate</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>0.371187</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>0.292606</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>0.435712</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>0.376864</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>0.225450</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   ID  MAE_univariate\n",
       "0   0        0.371187\n",
       "1   1        0.292606\n",
       "2   2        0.435712\n",
       "3   3        0.376864\n",
       "4   4        0.225450"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mae_df_univariate = res_df_univariate.groupby(\"ID\").apply(\n",
    "    lambda x: mean_absolute_error(x[\"test\"], x[\"pred\"])\n",
    ").reset_index()\n",
    "\n",
    "mae_df_univariate.columns = [\"ID\", \"MAE_univariate\"]\n",
    "mae_df_univariate"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2.2. Global-modelling LightAutoML"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Duplicate ID column for better feature generating\n",
    "train[\"id_2\"] = train[ID_COLUMN]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[10:34:19] Stdout logging level is DEBUG.\n",
      "[10:34:19] Task: multi:reg\n",
      "\n",
      "[10:34:19] Start automl preset with listed constraints:\n",
      "[10:34:19] - time: 3600.00 seconds\n",
      "[10:34:19] - CPU: 4 cores\n",
      "[10:34:19] - memory: 16 GB\n",
      "\n",
      "[18:05:37] Layer \u001b[1m1\u001b[0m train process start. Time left 3599.91 secs\n",
      "[18:05:38] Start fitting \u001b[1mLvl_0_Pipe_0_Mod_0_RFSklearn\u001b[0m ...\n",
      "[18:05:38] Training params: {'bootstrap': True, 'ccp_alpha': 0.0, 'max_depth': None, 'max_features': 'sqrt', 'max_leaf_nodes': None, 'max_samples': None, 'min_samples_leaf': 32, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 500, 'n_jobs': 4, 'oob_score': False, 'random_state': 42, 'warm_start': False, 'verbose': 0, 'criterion': 'mse'}\n",
      "[18:05:38] ===== Start working with \u001b[1mfold 0\u001b[0m for \u001b[1mLvl_0_Pipe_0_Mod_0_RFSklearn\u001b[0m =====\n",
      "[18:05:40] Score for RF model: -0.478922\n",
      "[18:05:40] ===== Start working with \u001b[1mfold 1\u001b[0m for \u001b[1mLvl_0_Pipe_0_Mod_0_RFSklearn\u001b[0m =====\n",
      "[18:05:43] Score for RF model: -0.477559\n",
      "[18:05:43] Fitting \u001b[1mLvl_0_Pipe_0_Mod_0_RFSklearn\u001b[0m finished. score = \u001b[1m-0.47824063661560884\u001b[0m\n",
      "[18:05:43] \u001b[1mLvl_0_Pipe_0_Mod_0_RFSklearn\u001b[0m fitting and predicting completed\n",
      "[18:05:43] Time left 3593.91 secs\n",
      "\n",
      "[18:05:44] Start fitting \u001b[1mLvl_0_Pipe_1_Mod_0_LinearL2\u001b[0m ...\n",
      "[18:05:44] Training params: {'tol': 1e-06, 'max_iter': 100, 'cs': [1e-05, 5e-05, 0.0001, 0.0005, 0.001, 0.005, 0.01, 0.05, 0.1, 0.5, 1, 5, 10, 50, 100, 500, 1000, 5000, 10000, 50000, 100000], 'early_stopping': 2, 'categorical_idx': [], 'embed_sizes': (), 'data_size': 226}\n",
      "[18:05:44] ===== Start working with \u001b[1mfold 0\u001b[0m for \u001b[1mLvl_0_Pipe_1_Mod_0_LinearL2\u001b[0m =====\n",
      "[18:05:44] Linear model: C = 1e-05 score = -0.5964374876210202\n",
      "[18:05:44] Linear model: C = 5e-05 score = -0.4531700575784085\n",
      "[18:05:44] Linear model: C = 0.0001 score = -0.4146961763297737\n",
      "[18:05:45] Linear model: C = 0.0005 score = -0.38449422448982795\n",
      "[18:05:45] Linear model: C = 0.001 score = -0.38138838560544014\n",
      "[18:05:45] Linear model: C = 0.005 score = -0.38019812717729135\n",
      "[18:05:45] Linear model: C = 0.01 score = -0.38034723995869585\n",
      "[18:05:45] Linear model: C = 0.05 score = -0.38041431355765454\n",
      "[18:05:45] ===== Start working with \u001b[1mfold 1\u001b[0m for \u001b[1mLvl_0_Pipe_1_Mod_0_LinearL2\u001b[0m =====\n",
      "[18:05:46] Linear model: C = 1e-05 score = -0.5906956397709\n",
      "[18:05:46] Linear model: C = 5e-05 score = -0.45173117819934433\n",
      "[18:05:46] Linear model: C = 0.0001 score = -0.4145036642322005\n",
      "[18:05:46] Linear model: C = 0.0005 score = -0.3849509035123634\n",
      "[18:05:47] Linear model: C = 0.001 score = -0.3813145757461596\n",
      "[18:05:47] Linear model: C = 0.005 score = -0.37985413506750626\n",
      "[18:05:47] Linear model: C = 0.01 score = -0.37999213463071496\n",
      "[18:05:47] Linear model: C = 0.05 score = -0.38003681603029926\n",
      "[18:05:47] Fitting \u001b[1mLvl_0_Pipe_1_Mod_0_LinearL2\u001b[0m finished. score = \u001b[1m-0.3800261491230324\u001b[0m\n",
      "[18:05:47] \u001b[1mLvl_0_Pipe_1_Mod_0_LinearL2\u001b[0m fitting and predicting completed\n",
      "[18:05:47] Time left 3589.22 secs\n",
      "\n",
      "[18:05:48] Start fitting \u001b[1mLvl_0_Pipe_2_Mod_0_CatBoost\u001b[0m ...\n",
      "[18:05:48] Training params: {'task_type': 'GPU', 'thread_count': 4, 'random_seed': 42, 'num_trees': 3000, 'learning_rate': 0.03, 'l2_leaf_reg': 0.01, 'bootstrap_type': 'Bernoulli', 'grow_policy': 'SymmetricTree', 'max_depth': 5, 'min_data_in_leaf': 1, 'one_hot_max_size': 10, 'fold_permutation_block': 1, 'boosting_type': 'Plain', 'boost_from_average': True, 'od_type': 'Iter', 'od_wait': 100, 'max_bin': 32, 'feature_border_type': 'GreedyLogSum', 'nan_mode': 'Min', 'verbose': 100, 'allow_writing_files': False, 'devices': '0'}\n",
      "[18:05:49] ===== Start working with \u001b[1mfold 0\u001b[0m for \u001b[1mLvl_0_Pipe_2_Mod_0_CatBoost\u001b[0m =====\n",
      "[18:05:49] 0:\tlearn: 4.9703982\ttest: 4.9996176\tbest: 4.9996176 (0)\ttotal: 43.1ms\tremaining: 2m 9s\n",
      "[18:05:53] 100:\tlearn: 3.1817923\ttest: 3.2535349\tbest: 3.2535349 (100)\ttotal: 4.01s\tremaining: 1m 55s\n",
      "[18:05:57] 200:\tlearn: 2.5726766\ttest: 2.6805614\tbest: 2.6805614 (200)\ttotal: 8.03s\tremaining: 1m 51s\n",
      "[18:06:01] 300:\tlearn: 2.2560121\ttest: 2.3947249\tbest: 2.3947249 (300)\ttotal: 12.1s\tremaining: 1m 48s\n",
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      "[18:06:22] 800:\tlearn: 1.6764093\ttest: 1.9538165\tbest: 1.9538165 (800)\ttotal: 32.9s\tremaining: 1m 30s\n",
      "[18:06:26] 900:\tlearn: 1.6219885\ttest: 1.9225213\tbest: 1.9225213 (900)\ttotal: 37.1s\tremaining: 1m 26s\n",
      "[18:06:30] 1000:\tlearn: 1.5738942\ttest: 1.8971965\tbest: 1.8971965 (1000)\ttotal: 41.2s\tremaining: 1m 22s\n",
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      "[18:06:55] 1600:\tlearn: 1.3703607\ttest: 1.8202220\tbest: 1.8202220 (1600)\ttotal: 1m 5s\tremaining: 57.6s\n",
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      "[18:07:51] bestTest = 1.774010135\n",
      "[18:07:51] bestIteration = 2999\n",
      "[18:07:51] ===== Start working with \u001b[1mfold 1\u001b[0m for \u001b[1mLvl_0_Pipe_2_Mod_0_CatBoost\u001b[0m =====\n",
      "[18:07:52] 0:\tlearn: 4.9945826\ttest: 4.9698499\tbest: 4.9698499 (0)\ttotal: 41.8ms\tremaining: 2m 5s\n",
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      "[18:09:30] 2400:\tlearn: 1.1906539\ttest: 1.7857203\tbest: 1.7857203 (2400)\ttotal: 1m 38s\tremaining: 24.5s\n",
      "[18:09:34] 2500:\tlearn: 1.1705045\ttest: 1.7827000\tbest: 1.7827000 (2500)\ttotal: 1m 42s\tremaining: 20.4s\n",
      "[18:09:38] 2600:\tlearn: 1.1510307\ttest: 1.7808157\tbest: 1.7808028 (2598)\ttotal: 1m 46s\tremaining: 16.3s\n",
      "[18:09:42] 2700:\tlearn: 1.1323293\ttest: 1.7789892\tbest: 1.7789676 (2697)\ttotal: 1m 50s\tremaining: 12.2s\n",
      "[18:09:46] 2800:\tlearn: 1.1142749\ttest: 1.7767626\tbest: 1.7767626 (2800)\ttotal: 1m 54s\tremaining: 8.14s\n",
      "[18:09:50] 2900:\tlearn: 1.0964777\ttest: 1.7755168\tbest: 1.7755025 (2899)\ttotal: 1m 58s\tremaining: 4.05s\n",
      "[18:09:54] 2999:\tlearn: 1.0793822\ttest: 1.7741527\tbest: 1.7741169 (2997)\ttotal: 2m 2s\tremaining: 0us\n",
      "[18:09:54] bestTest = 1.774116879\n",
      "[18:09:54] bestIteration = 2997\n",
      "[18:09:54] Shrink model to first 2998 iterations.\n",
      "[18:09:54] Fitting \u001b[1mLvl_0_Pipe_2_Mod_0_CatBoost\u001b[0m finished. score = \u001b[1m-0.24088612521804945\u001b[0m\n",
      "[18:09:54] \u001b[1mLvl_0_Pipe_2_Mod_0_CatBoost\u001b[0m fitting and predicting completed\n",
      "[18:09:54] Time left 3342.18 secs\n",
      "\n",
      "[18:09:54] \u001b[1mLayer 1 training completed.\u001b[0m\n",
      "\n",
      "[18:09:54] Blending: optimization starts with equal weights and score \u001b[1m-0.31863480146881884\u001b[0m\n",
      "[18:09:54] Blending: iteration \u001b[1m0\u001b[0m: score = \u001b[1m-0.24088612521804945\u001b[0m, weights = \u001b[1m[0. 0. 1.]\u001b[0m\n",
      "[18:09:55] Blending: iteration \u001b[1m1\u001b[0m: score = \u001b[1m-0.24088612521804945\u001b[0m, weights = \u001b[1m[0. 0. 1.]\u001b[0m\n",
      "[18:09:55] Blending: no score update. Terminated\n",
      "\n",
      "[18:09:55] \u001b[1mAutoml preset training completed in 257.95 seconds\u001b[0m\n",
      "\n",
      "[10:40:24] Model description:\n",
      "Final prediction for new objects (level 0) = \n",
      "\t 1.00000 * (2 averaged models Lvl_0_Pipe_2_Mod_0_CatBoost) \n",
      "\n"
     ]
    }
   ],
   "source": [
    "oof_pred_seq = automl.fit_predict(train, roles=global_modelling_roles, verbose=4)\n",
    "seq_test = automl.predict(train, return_raw=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "```seq_test``` соis consisted of:\n",
    "   - seq_test.date — base date, from which predictions are made\n",
    "   - seq_test.id — id of time series\n",
    "   - seq_test.data — predictions themselves"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can collect these values to the df.DataFrame:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ID</th>\n",
       "      <th>date</th>\n",
       "      <th>pred</th>\n",
       "      <th>value</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>2025-05-24</td>\n",
       "      <td>2.384080</td>\n",
       "      <td>1.581092</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0</td>\n",
       "      <td>2025-05-25</td>\n",
       "      <td>3.279628</td>\n",
       "      <td>2.376163</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0</td>\n",
       "      <td>2025-05-26</td>\n",
       "      <td>3.530711</td>\n",
       "      <td>2.627754</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0</td>\n",
       "      <td>2025-05-27</td>\n",
       "      <td>3.079974</td>\n",
       "      <td>2.105468</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0</td>\n",
       "      <td>2025-05-28</td>\n",
       "      <td>2.362342</td>\n",
       "      <td>1.969833</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>145</th>\n",
       "      <td>4</td>\n",
       "      <td>2025-06-18</td>\n",
       "      <td>1.874377</td>\n",
       "      <td>2.149213</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>146</th>\n",
       "      <td>4</td>\n",
       "      <td>2025-06-19</td>\n",
       "      <td>1.947542</td>\n",
       "      <td>1.807998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>147</th>\n",
       "      <td>4</td>\n",
       "      <td>2025-06-20</td>\n",
       "      <td>2.211135</td>\n",
       "      <td>1.810103</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>148</th>\n",
       "      <td>4</td>\n",
       "      <td>2025-06-21</td>\n",
       "      <td>2.608910</td>\n",
       "      <td>1.941590</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>149</th>\n",
       "      <td>4</td>\n",
       "      <td>2025-06-22</td>\n",
       "      <td>3.128166</td>\n",
       "      <td>2.590021</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>150 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     ID       date      pred     value\n",
       "0     0 2025-05-24  2.384080  1.581092\n",
       "1     0 2025-05-25  3.279628  2.376163\n",
       "2     0 2025-05-26  3.530711  2.627754\n",
       "3     0 2025-05-27  3.079974  2.105468\n",
       "4     0 2025-05-28  2.362342  1.969833\n",
       "..   ..        ...       ...       ...\n",
       "145   4 2025-06-18  1.874377  2.149213\n",
       "146   4 2025-06-19  1.947542  1.807998\n",
       "147   4 2025-06-20  2.211135  1.810103\n",
       "148   4 2025-06-21  2.608910  1.941590\n",
       "149   4 2025-06-22  3.128166  2.590021\n",
       "\n",
       "[150 rows x 4 columns]"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "freq = pd.infer_freq(train[DATE_COLUMN].iloc[:10])\n",
    "date_list = [seq_test.date[0] + pd.Timedelta(1+i, unit=freq) for i in range(HORIZON)]\n",
    "date_list = date_list * len(seq_test.id)\n",
    "pred_list = list(seq_test.data.reshape(-1))\n",
    "id_list = np.repeat(seq_test.id, HORIZON)\n",
    "\n",
    "df_dict = {\n",
    "    \"ID\": id_list,\n",
    "    \"date\": date_list,\n",
    "    \"pred\": pred_list\n",
    "}\n",
    "\n",
    "res_df_global = pd.DataFrame(df_dict)\n",
    "res_df_global = res_df_global.merge(test, on=[\"ID\", \"date\"])\n",
    "\n",
    "res_df_global"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Check MAE for all time series:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ID</th>\n",
       "      <th>MAE_global</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>0.344390</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>0.227540</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>0.477782</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>0.342722</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>0.193969</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   ID  MAE_global\n",
       "0   0    0.344390\n",
       "1   1    0.227540\n",
       "2   2    0.477782\n",
       "3   3    0.342722\n",
       "4   4    0.193969"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mae_df_global = res_df_global.groupby(\"ID\").apply(\n",
    "    lambda x: mean_absolute_error(x[\"value\"], x[\"pred\"])\n",
    ").reset_index()\n",
    "\n",
    "mae_df_global.columns = [\"ID\", \"MAE_global\"]\n",
    "mae_df_global"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Compare MAE for two strategies (univariate/local- and global-modelling):"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ID</th>\n",
       "      <th>MAE_global</th>\n",
       "      <th>MAE_univariate</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>0.344390</td>\n",
       "      <td>0.371187</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>0.227540</td>\n",
       "      <td>0.292606</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>0.477782</td>\n",
       "      <td>0.435712</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>0.342722</td>\n",
       "      <td>0.376864</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>0.193969</td>\n",
       "      <td>0.225450</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   ID  MAE_global  MAE_univariate\n",
       "0   0    0.344390        0.371187\n",
       "1   1    0.227540        0.292606\n",
       "2   2    0.477782        0.435712\n",
       "3   3    0.342722        0.376864\n",
       "4   4    0.193969        0.225450"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mae_df_global.merge(mae_df_univariate, on=[\"ID\"])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Lastly, get a graph of models' predictions in comparison with each other and the true values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1728x1080 with 5 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "LAST_TRAIN_N = 120\n",
    "\n",
    "num_ids = len(df[ID_COLUMN].value_counts())\n",
    "subplots_num_columns = 2\n",
    "subplots_num_rows = num_ids // 2 + num_ids % 2\n",
    "fig, ax = plt.subplots(\n",
    "    subplots_num_rows, \n",
    "    subplots_num_columns, \n",
    "    figsize=(24, 5 * subplots_num_rows)\n",
    ")\n",
    "\n",
    "for i, ts_id in enumerate(df[ID_COLUMN].unique()):\n",
    "    i_row = i // 2\n",
    "    i_col = i % 2\n",
    "    \n",
    "    current_train = train[train[ID_COLUMN] == ts_id]\n",
    "    current_res_df_univariate = res_df_univariate[res_df_univariate[ID_COLUMN] == ts_id]\n",
    "    current_res_df_global = res_df_global[res_df_global[ID_COLUMN] == ts_id]\n",
    "    \n",
    "    ax[i_row, i_col].plot(current_train[DATE_COLUMN][-LAST_TRAIN_N:], current_train[TARGET_COLUMN][-LAST_TRAIN_N:], c='b', label='train')\n",
    "    ax[i_row, i_col].plot(current_res_df_univariate[DATE_COLUMN], current_res_df_univariate[\"test\"], c='g', label='test')\n",
    "    ax[i_row, i_col].plot(current_res_df_univariate[DATE_COLUMN], current_res_df_univariate[\"pred\"], c='r', label='pred univariate')\n",
    "    ax[i_row, i_col].plot(current_res_df_global[DATE_COLUMN], current_res_df_global[\"pred\"], c='indigo', label='pred global')\n",
    "\n",
    "    ax[i_row, i_col].title.set_text(f\"TS with ID {ts_id}\")\n",
    "    ax[i_row, i_col].legend()\n",
    "    \n",
    "axes_to_del = i_row * subplots_num_rows + i_col * subplots_num_columns - num_ids\n",
    "for i in range(axes_to_del):\n",
    "    i_row = (subplots_num_rows - 1) - i // 2\n",
    "    i_col = (subplots_num_columns - 1) - i % 2\n",
    "    fig.delaxes(ax[i_row][i_col])\n",
    "    \n",
    "plt.show();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
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    "### Additional materials"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- [Official LightAutoML github repo](https://github.com/sb-ai-lab/LightAutoML)\n",
    "- [LightAutoML documentation](https://lightautoml.readthedocs.io/en/latest)"
   ]
  }
 ],
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